Full-Time

Assistant Scientist

Quantum Materials

Updated on 9/3/2026

Argonne National Laboratory

Argonne National Laboratory

5,001-10,000 employees

Advanced scientific research and computing facilities

No salary listed

Company Does Not Provide H1B Sponsorship

Woodridge, IL, USA

In Person

On-site role based in Lemont, Illinois; remote work not available.

PhD

Category
Academic & Institutional Research (1)

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Requirements
  • Ph.D. in physics, materials science, chemistry, or a closely related discipline with 2+ years of postdoc experience
  • Postdoctoral research experience within the field of quantum materials
  • Expertise in single crystal growth of inorganic quantum materials
  • Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory
  • Ability to model Argonne’s core values: Impact, Safety, Respect, Integrity, and Teamwork
Responsibilities
  • Establish and lead an independent research program while working closely with scientists across the Quantum States in Crystalline Matter Group and the broader Materials Science Division community
  • Develop innovative research directions in quantum materials and publish impactful results in leading scientific journals
  • Contribute to proposal development
  • Mentor postdoctoral researchers, graduate students, and visiting scientists
  • Contribute to the QSCM Group’s ongoing research efforts and help shape its future scientific directions through development of novel research initiatives that complement and expand the group’s portfolio
  • Collaborate with Argonne and regularly conduct experiments at world-leading user facilities such as the Advanced Photon Source and the Center for Nanoscale Materials; engage in collaborations with external facilities (e.g., neutron-scattering centers at Oak Ridge National Laboratory and the National Institute of Standards and Technology)
Desired Qualifications
  • Expertise in crystal structure determination using X-ray diffraction
  • Experience with bulk property characterization techniques including electrical transport, specific heat, and magnetic measurements
  • Familiarity with conducting or collaborating on experiments at major national user facilities, including synchrotron and neutron-scattering centers
Argonne National Laboratory

Argonne National Laboratory

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Argonne National Laboratory advances scientific discovery and sustainability by providing access to large-scale research facilities and high-performance computing for government, academia, and industry partners. Researchers use the Advanced Photon Source for atomic-level materials studies and the Argonne Leadership Computing Facility for complex simulations and data analysis. The lab differentiates itself through its shared-use, multi-institution partnerships and a focus on eco-innovation, net-zero goals, and AI accelerator development. Its aim is to address real-world energy, materials, and data science challenges by combining cutting-edge infrastructure with collaborative research efforts.

Company Size

5,001-10,000

Company Stage

Grant

Total Funding

$19.7M

Headquarters

Lemont, Illinois

Founded

1946

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Simplify Jobs

Simplify's Take

What believers are saying

  • UChicago Argonne LLC won a renewed DOE contract in 2026 for five years.
  • 2026 launch of ChemGraph, GridMind, and AI inference services deepens Argonne's relevance.
  • Activated Materials Lab opened in 2026, expanding nuclear fuels research and user-facility demand.

What critics are saying

  • DOE's FY2027 request cuts Argonne funding about $155.8 million, hitting programs and construction.
  • 2025 buyouts showed staff pressure; more layoffs follow if Congress accepts budget cuts.
  • A prolonged federal reset or shutdown threatens APS, Aurora utilization, and Argonne's operating model.

What makes Argonne National Laboratory unique

  • Aurora and APS create a rare AI-plus-X-ray discovery stack for 2026 science.
  • Chain Reaction Innovations embeds startups inside Argonne with facilities, mentors, and DOE funding.
  • Q-NEXT and other DOE centers keep Argonne central to U.S. quantum research.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Paid Vacation

Paid Sick Leave

Paid Holidays

Remote Work Options

Flexible Work Hours

401(k) Retirement Plan

401(k) Company Match

Professional Development Budget

Wellness Program

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-2%

2 year growth

-2%
Associated Press
Jul 7th, 2026
Argonne's ChemGraph uses AI to automate computational chemistry workflows

Researchers at the US Department of Energy's Argonne National Laboratory have developed ChemGraph, an open-source framework that uses artificial intelligence to automate computational chemistry workflows. The tool provides a natural language interface, allowing researchers to describe scientific problems in plain language, which the system then maps onto computational tasks and analyses. ChemGraph was developed using resources at the Argonne Leadership Computing Facility, including the Aurora exascale supercomputer. The framework uses AI agents to handle different workflow tasks, from planning to execution and data aggregation. It calls appropriate scientific tools to reduce the risk of AI hallucination, using AI to run physics-based simulations rather than relying solely on existing knowledge. The framework supports applications in combustion efficiency, critical materials, and next-generation batteries, and complements DOE's Genesis Mission to accelerate science through AI.

The Register
May 27th, 2026
Argonne National Laboratory launches private AI inference service using spare supercomputer capacity

The US Department of Energy's Argonne National Laboratory has launched an AI inference service using spare supercomputing capacity to support researchers across DoE labs and the Genesis Mission. The service runs on two clusters: Sophia, with 192 Nvidia A100 GPUs, and Metis, featuring 32 SambaNova SN40L AI accelerators. The platform provides secure access to various large language models, including OpenAI's GPT-OSS, Google's Gemma, and Meta's Llama, through a chatbot-like portal. Researchers are using the service to analyse experimental data in real time, including predicting plasma disruptions in fusion energy research and processing data from particle accelerators and telescopes. Argonne plans to extend the service to its Nvidia GH200-based Tara and B200-based Minerva systems, enabling scientists to experiment with AI without building their own infrastructure.

Business Wire
Mar 26th, 2026
Argonne Lab develops GridMind AI agent to support power grid operators

Researchers at the US Department of Energy's Argonne National Laboratory have developed GridMind, an agentic AI system designed to assist power grid operators through natural language interaction. The system functions as a reasoning co-pilot for control rooms, simplifying complex grid management tasks. GridMind employs a multi-agent architecture where specialised AI agents handle different functions, such as power scheduling and weather-based contingency planning. Large language models coordinate these agents to analyse situations, reason across different tasks and provide explainable recommendations. The system transforms technical analysis into conversational support whilst maintaining rigorous accuracy. Tests on standard power grid models demonstrated that GridMind consistently produced correct results across multiple state-of-the-art language models. The technology aims to accelerate decision-making by integrating disconnected workflows into a coherent reasoning engine.

Yahoo Finance
Mar 11th, 2026
AI adviser helps Argonne's robotic lab discover advanced electronic materials in just 64 experiments

A research team led by the US Department of Energy's Argonne National Laboratory has developed an AI adviser that optimises machine learning algorithms during autonomous experiments, accelerating discovery of advanced electronic materials. The system was applied to Polybot, Argonne's AI-guided robotic laboratory, to investigate mixed ion-electron conducting polymers for wearable electronics and energy storage. The adviser evaluates algorithm performance in real time and communicates insights to scientists who refine experimental plans. It reduced the study to just 64 experiments from over 4,300 possible combinations. During testing, the adviser suggested switching AI algorithms, leading to significant performance improvements, and identified deposition speed as a key performance driver. The research was published in Nature Chemical Engineering and included collaborators from the University of Chicago, Lawrence Berkeley National Laboratory and other institutions.

Argonne National Laboratory
Jun 2nd, 2022
5 clean energy startups chosen for Argonne’s Chain Reaction Innovations - Chain Reaction Innovations

An energy and science incubator for transformative technologies